The degree to which matching is required generally depends upon how well the acquisition has been repeated from one survey to the next. Variability within or between datasets should, where possible, be compensated by appropriate processing algorithms, rather than by survey matching.
Types of matching defined:
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Deterministic matching
Often used to normalize the wavelet for surveys that used different acquisition configuration. A common reference wavelet is defined, and filters created that match the farfield signatures of each survey to the reference. This can be performed in an angular-dependent fashion, if required.
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Global matching
Uses a single statistically computed matching operator to cause one survey to better match another in amplitude, phase, and timing. The operator may be frequency invariant or vary with frequency.
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Non-rigid matching
A trace-by-trace matching, operates on pairs of collocated traces from the two surveys. For each pair, a unique operator is designed to cause one trace of the pair to better match the other. A smoothness criterion is typically imposed to ensure that the operators are spatially and temporally consistent.